Knitted Fabrics Research Articles

The Effect of Embroidery Machines’ Variables with Decorative Cords on the Properties of Knitted Fabrics

The Effect of Embroidery Machines’ Variables with Decorative Cords on the Properties of Knitted Fabrics

Investigating the Impact of Air Permeability and Thermal Properties on Rib Knit Structures

Factors influencing the comfort and performance of knitted fabrics can be investigated to enhance the understanding and development of functional accessories. Issues related to the thermal regulation and moisture management of these materials are systematically explored in this research. Additionally, the effects of fibre type, yarn properties, fabric variables, and finishing methods are examined through the evaluation of physical properties relevant to the comfort of rib knit structures, particularly in sportswear design. 1x1 Rib knit 1structures were created using polyester spun, cotton spun, polyester filament, and viscose filament yarns with varying linear densities employing a KH-323N computerized flatbed knitting machine. Evaluations of physical properties, thermal characteristics, air permeability, antibacterial efficiency, and hydrophilic finish were conducted following ASTM standards and specific testing methods to thoroughly assess the quality and performance of the fabric. Significant insights into the physical and comfort properties of the fabrics were provided by the results. Varying thermal and air permeability characteristics were demonstrated by polyester-cotton and viscose-cotton fabrics. Thermal resistance and conductivity are influenced by filament denier, loop length, and knit structure, while these same factors affect air permeability. Air permeability is also impacted by finishing treatments, thereby highlighting the complex interplay between fabric properties and comfort. Advanced finishing techniques and novel fibre blends could be explored in future research to further optimize fabric comfort properties.

Optimized Gabor Filter Banks and Autoencoder Models for Enhanced Knitted Fabric Defect Detection

There is a high need for an automated system to detect fabric defects, as the current manual methods used in the garment industries in Nepal are unreliable and costly. Previous research has focused on specific fabric defects rather than overall fabric defects efficiently. This research employs two autoencoder models to identify different defects across different types of knitted fabrics, utilizing two datasets: the SFDG dataset and a custom dataset prepared from Butwal’s garment industries. The models benefit from a carefully designed Gabor filter bank to examine fabric compositions. This filter bank is fine-tuned by modifying parameters, wavelength, and orientation to detect varieties of defects in knitted fabrics. These models get feature representations from the Gabor filter bank’s outputs and help the system adapt to different types of defect patterns, making defect detection more reliable and accurate. The nearest neighbor density estimator finds possible defects and marks on the fabric images. The model's effectiveness and strength are shown by validating it on different types of knitted fabrics, including plain and patterned fabrics, using evaluation metrices like cTPR and ROC AUC. The first model achieves a cTPR of 0.879 and an AUC score of 0.947, while the second model achieves a cTPR of 0.899 and an AUC score of 0.958.

Analyzing the Factors by One-Way ANOVA Associated with Plain Weft Knitted Fabrics’ Production

Bangladesh has achieved a significant reputation for RMG exporting over the last three decades, particularly in knitwear. The knitwear sector is one of the self-supporting sectors of Bangladesh, which could meet 90% of the fabric requirements. However, there is an empirical relationship between machine diameter and fabric diameter. It’s assumed that the machine diameter determines the fabric diameter. Therefore, the objectives of the study were to test the significance of average shifting in fabric diameter from machine diameter and the overall effect of machine diameter on fabric diameter. Empirical research has been conducted for such an investigation. This study was carried out with a few factories and a full lot of each factory was inspected. Based on the collected data, diameters of machines were grouped into three levels to understand the variation of fabric diameters. Then, SPSS software was used to analyze the collected data, applying one sample t test and one-way ANOVA. However, the result of the analysis revealed that machine diameter has no effect but indicative means reduction were found in fabric diameters. In the future, more comprehensive studies could be done by including larger data. But now, these findings will help all the personnel related to the quality and production of knitted fabric.

Evaluation of the Bursting Strength and Pilling Properties of Knitted Fabrics Produced from Recycled Yarns with Cotton Hard Waste

Abstract In terms of sustainability, the textile industry has a significant impact because of intense mass consumption, fast fashion trends, short-term use of products, and thus the textile industry increases textile waste. Basic textile wastes are in solid forms of fibers, yarns, fabrics, cardboard, plastics, dyes, and chemicals containing wastewater, as well as gaseous wastes that cause emissions that release after textile processes. Recycling is the best solution for all textile wastes. In the recycling process of cotton, preconsumption wastes are generated in yarn production and the following production departments, whereas postconsumption wastes are used after classification according to both the structure and the color of the incoming wastes. Cotton hard waste is used at different blend ratios, and this study aims to reveal the effects of waste material on both the bursting strength and pilling properties of fabrics knitted with rotor yarns in different yarn counts. In the scope of sustainability, the findings show that the use of cotton hard waste at up to a 50 % ratio in circular knitted fabrics does not adversely affect the fabric’s bursting strength and pilling properties.

An approach to automatic fault detection in four-point system for knitted fabric with our benchmark dataset Isl-Knit

Knit fabric is one of the dominating fabric types for wearable textile across the whole world and during the production of knit fabric, faults created by different reasons cause difficulties in the subsequent process. The existing fault detection process in the knitting industry is done manually by the human naked eye. To detect faults automatically, deep learning-based models are very efficient and can reduce the workload for fabric inspection. However, implementing a deep learning-based model for fabric fault detection needs a large number of images with different types of knit fabric faults from real-world scenarios to train and for better performance. Most of the existing fabric fault datasets are based on woven fabric, which cannot be used for training because the faults of woven fabric and knit fabrics are completely different. In this research, we propose a new dataset named ISL-Knit. It is a benchmark dataset for knit fabric faults collected from different knit dyeing industries in Bangladesh. Our dataset contains high-resolution images of grey fabric and dyed fabric annotated with 7 types of faults. To provide correct annotation, all images of faults are annotated and verified with the proper reference which can be a great tool for boosting up deep learning-based models for automatic knit fabric fault detection in the textile field. A comparison of the accuracy of the deep learning-based model by training with our proposed dataset and existing knit fabric fault dataset is also done. To develop an automatic fault detection system, we trained the YOLOv5 models with our dataset, considering different image sizes. For real-world implementation, the best models are selected considering mAP and inference time. YOLOv5 models are implemented in Raspberry Pi with a Raspberry Pi camera, a laptop with no dedicated GPU, and a laptop with a dedicated GPU with a web camera to observe the performance. Finally, an automated four-point inspection system is developed by calibrating the camera to generate the score representing the quality of fabrics. The implementation represents the feasibility of a deep learning-based model in knit fabric fault detection, considering the cost and accuracy.

Development of Laminated Knitted Fabrics with Improved Performance Properties for Automotive Upholstery

Development of Laminated Knitted Fabrics with Improved Performance Properties for Automotive Upholstery

Simulation of the tensile behaviour of biaxial knitted fabrics produced based on rib structure using a macro constitutive model

This study presents a macro-scale constitutive model to simulate the tensile behaviour of biaxial weft knitted fabrics produced based on a 1 × 1 rib structure. Fabrics were produced using polyester yarns as stitch yarns and nylon yarns as straight yarns in a modern flat knitting machine. Stress–strain curves of 1 × 1 rib structure and corresponding biaxial knitted fabric were measured in three different directions (course, wale and 45 degrees) on a tensile tester. Based on extracted results, a constitutive equation was proposed for macro modelling of biaxial knitted fabrics. The stiffness matrix of the biaxial knitted fabrics was assumed to be a combination of the stiffness matrix of 1 × 1 rib and reinforcement yarns. A UMAT subroutine was provided to implement the constitutive behaviour in Abaqus software. To evaluate the accuracy of the proposed model, fabric tensile behaviour in 22.5° and 67.5° directions were simulated and compared with experimental results. The results showed that the macro model can successfully predict the tensile behaviour of the biaxial weft knitted fabric in different directions.

Enhanced thermoregulation performance of knitted fabrics using phase change material incorporated thermoplastic polyurethane and cellulose acetate nanofibers

AbstractNanofibers act as carriers in systems containing functional materials produced via electrospinning method. By this way, it is possible to transport functional materials with polymer nanofibers, besides having a large surface area compared to their volume, the encapsulation process, which includes complex preparation processes, is eliminated here, and functional materials such as phase‐change materials (PCMs) can be conveniently integrated directly into the carrier material by electrospinning method. The resulting nanofiber membrane can also be used in combination with textile fabrics. This study aims to develop PCM containing nanofibrous membrane coated knitted fabric structures with heat regulation capabilities. Two types of PCMs, hexadecane and octadecane loaded into thermoplastic polyurethane (TPU) and cellulose acetate (CA) nanofibers, directly electrospun on cotton (CO), cotton/polyester (CO/PES), cotton/acrylic (CO/PAC) knitted fabrics for thermoregulation. These nanofiber‐coated fabrics were characterized by scanning electron microscopy (SEM) and differential scanning colorimetry (DSC), and their comfort properties were evaluated by water vapor and air permeability tests and compared with a commercial microcapsule impregnated fabric. According to DSC results, PCM incorporated CA nanofibers had better heat storage capacity than TPU nanofibers and microcapsule applied fabrics. Although PCM‐loaded CA nanofibers may not block airflow as effectively as TPU nanofibers, when a proper coating is achieved air permeability can be decreased to 21.70 L/m2/s, along with a heat storage capacity of 26.38 J/g and still having permeability to water vapor (%40).Highlights Phase change materials were integrated directly to the carrier material by electrospinning PCM integrated nanofiber coating reduced air permeability PCM integrated nanofiber coating did not block water vapor permeability Electrspun cellulose acetate +PCM coating had better heat storage capacity

Study on the promotion multiple of blood flow velocity on human epidermal microcirculation of volcanic rock polymer fiber seamless knitted fabric

Abstract As a material that can release infrared rays, volcanic rock polymer fibers can be used in textiles to improve human microcirculation, which is helpful to relieve chronic inflammatory diseases such as perishoulder arthritis. In this article, there are two different kinds of exterior yarns. Volcanic rock blended polyester, volcanic rock blended polyamide, polyester and polyamide are chosen as the material type of exterior yarn Ⅰ, whereas the material type of exterior yarn II is conductive polyamide yarn. The exterior yarn feed ratio of exterior yarn Ⅰ and exterior yarn II is designed as 8:0, 7:1 and 6:2 when weft plain stitch, 1 + 1 mock rib and 1 + 3 mock rib are used as the knitted structure of the fabric. According to the three-factor four-level orthogonal experimental design method, the sample protocol was established, and 16 knitted sample fabrics were produced. Then, the promotion multiple of blood flow velocity on human epidermal microcirculation of each sample was tested and analyzed. The results show that the promotion multiple of blood flow velocity on human epidermal microcirculation of the fabrics woven by volcanic rock polymer fibers is better than that of the blank control group, and the difference between fabrics with different volcanic rock polymer fibers is small. The higher the proportion of exterior yarn Ⅰ is, the better the promotion multiple of blood flow velocity on human epidermal microcirculation of fabric will be. The effect of knitted structure on the promotion multiple of blood flow velocity on human epidermal microcirculation of fabrics is not obvious. This study provides reference for the design of medical or health textiles for chronic inflammatory diseases.

Unravelling the mechanics of knitted fabrics through hierarchical geometric representation

Knitting interloops one-dimensional yarns into three-dimensional fabrics that exhibit behaviour beyond their constitutive materials. How extensibility and anisotropy emerge from the hierarchical organization of yarns into knitted fabrics has long been unresolved. We seek to unravel the mechanical roles of tensile mechanics, assembly and dynamics arising from the yarn level on fabric nonlinearity by developing a yarn-based dynamical model. This physically validated model captures the mechanical response of knitted fabrics, analogous to flexible metamaterials and biological fibre networks due to geometric nonlinearity within such hierarchical systems. Fabric anisotropy originates from observed yarn–yarn rearrangements during alignment dynamics and is topology-dependent. This yarn-based model also provides a design space of knitted fabrics to embed functionalities by varying geometric configuration and material property in instructed procedures compatible to machine manufacturing. Our hierarchical approach to build up a knitted fabric computationally modernizes an ancient craft and represents a first step towards mechanical programmability of knitted fabrics in wide engineering applications.

An Investigation of Bursting Strength on Single Jersey Weft Knitted Fabrics

This paper investigates the bursting strength performance of single jersey weft knitted fabrics. The objective of the study is to find out the impact of the yarn count ,stitch length , stitch density, fabric thickness, loop shape factor, tightness factor ,GSM and porosity on the bursting strength of the single jersey weft knitted fabric. The experimental results have been statistically evaluated with Analysis ofVariance (ANOVA) test , Results show thatstitch length , stitch density, fabric thickness, loop shape factor, tightness factor ,GSM and porosity areeffective on bursting strength and individual ANOVA test results show that stitch density , fabric thickness , tightness factor , GSM and porosity are Individually effective on bursting strength .the GSM parameter of the fabric is fundamental for bursting strength , the correlation relation and R square values of GSM with bursting strength found to be in order 0.839& 0.9438

Bioinspired Multilayered Knitted Fabric with Directional Water Transport and Collection for Personal Sweat Management.

Effective sweat management fabric for sportswear facilitates sweat removal from the skin and elevates the comfort for human. However, when the body is in a strong hot and humid environment or after strenuous exercise, the sweat management fabric will be totally wetted and saturated quickly. As a result, excess sweat cannot be absorbed effectively by the garment, which creates obvious stickiness and heaviness. In this paper, a directional water transport and collection multilayered knitted fabric (DWTCF) is prepared by plasma pretreatment technology and screen coating. The treelike water transport network inspired from nature is designed in order to drive the liquid flow along the channels. By surface modification, branched hydrophilic flow paths are fabricated, and other regions are hydrophobic. As a demonstration, DWTCF has been injected with water to observe the liquid transport behavior. During the experiment, 76.7% liquid is collected by DWTCF, but there is just 0.06% collected by an ordinary knitted fabric. The weight increase of the ordinary fabric is 555.4% larger than that of DWTCF. Specifically, DWTCF utilizes the wetting and pressure-gradient-induced interfacial tension as well as the gravitational effect to facilitate the fluid motion along the hydrophilic channel, in addition to the capillarity present in the fabric structure. This study provides a new idea to develop directional water transport and collection fabric to solve the moisture absorption saturation problem of the fabric, especially for conditions requiring intense sweating.

Effect of hydrophilic and hydrophobic treatments on bloodstain patterns of drip stains on knitted cotton and polyester fabrics

ABSTRACT Textiles are one of the most frequently collected items at crime scenes. Even so, the mechanisms that create bloodstains on textiles are not well understood. This is likely due to the wide range of textiles and the many surface treatments given to them to enhance their performance. In this study, the final appearance of 50 μl passive drip stains on four in-house knitted apparel textiles (scoured cotton, hydrophobic cotton, hydrophilic polyester and hydrophobic polyester) was investigated. The yarns used to make the knits were 167 dTex polyester filament and 342 dTex cotton staple yarns. They were knitted on the same knitting machine under nominally identical conditions. The area of bloodstains on the scoured cotton knit fabrics was 46 mm2 and 30 mm2 on the hydrophobic cotton. i.e. the stains on the hydrophilic cotton were 50% larger than on the hydrophobic cotton. The bloodstains on hydrophobic polyester were only 15.6 mm2, but were 242 mm2 on hydrophilic polyester, i.e. 15 times larger. The stain areas on the polyester were both smaller (hydrophobic finish) and larger (hydrophilic finish) than on the cotton fabrics. It is shown that these typical chemical treatments play a much more important role on bloodstain areas than fibre type or fabric construction.

Efficiency analysis in knitted fabric portfolio management using DEA

Abstract Purpose The purpose of this paper is to develop a decision-making protocol to meet the new requirements in an atypical panorama, such as the economic instability, in the textile industry. Design/methodology/approach The methodology consists of analyzing technical criteria, costing parameters and efficiency scores of knitted fabrics using the data envelopment analysis (DEA) and classification and regression (C&R) trees models, together with statistical techniques. From these tools, it is possible to guide the portfolio management of these products in a textile company, identifying those that are inefficient and require immediate management measures. The results are expected to be replicated in other companies because the DEA and C&R trees analytical procedures are applicable to different portfolios, whether in the same industry or not. Findings The results allowed identifying inefficient textile products regarding the input-output relationship and the main technical reasons related to the most significant inefficiencies, such as fiber composition and knitted fabrics rapports used in manufacturing. Originality/value DEA and C&R trees, in combination with the study of textile technical parameters, can be fundamental to investigating the efficiency and profitability of industries in periods of economic instability or other adverse situations. In addition, it is noteworthy that there are practically no studies in the literature on DEA applied in the textile industry, indicating excellent development potential.

Study of Thermal Comfort Characteristics of Bi-layer Knitted Fabrics Made by Various Types of Spinning System Yarns

Study of Thermal Comfort Characteristics of Bi-layer Knitted Fabrics Made by Various Types of Spinning System Yarns

Synthesis and Characterization of ZnO and TiO2 Hybrid Coatings for Textile UV Anti-Aging Protection.

The aim of this study was to prepare and characterize thin hybrid films on polyurethane-coated knitted fabrics and to achieve satisfactory color fastness to artificial light. Sol-gel-derived hybrid thin films were deposited via the dip-coating of 3-glycidoxypropiltrimethoxysilane. Titanium dioxide (TiO2) and zinc oxide (ZnO) nanopowders were added to compensate for the insufficient aging resistance, which manifests itself in low color fastness and is one of the most frequent complaints from manufacturers of coated marine fabrics (yachts, boats, etc.). The optimum processing conditions were determined by varying the concentration of precursors and auxiliaries, the mass concentration of TiO2 and ZnO nanopowders, the drawing speed, and the methods and process of fabric treatment. The hybrid films were also characterized using scanning electron microscopy and Fourier transform infrared spectroscopy with attenuated total internal reflection, while Spectraflash SF 300 investigated color fastness. After 300 h of exposure in a xenon chamber, the thin hybrid films showed good color fastness and good resistance to washing cycles. The sol-gel treatment proved to be a successful answer to the manufacturers' need for the post-treatment of polyurethane-coated knitted fabrics against UV radiation for use in the marine sector (yachts, speedboats, etc.).

Meso-macro deformation investigation for biaxial knitted textile based pouch motor

A detailed knowledge of the deformation behavior of pouch motor contracting actuators (PMCA) improves their performance, and researchers are always looking for materials and structures that can increase the actuator’s performance by better controlling these deformations. In this article, a novel PMCA is fabricated using three-dimensional (3D) knitting technology, and its constitutive material is spectra as a non-stretch yarn. However, the final fabric (loop structure) is stretchable in the course direction and non-stretchable in the wale direction (anisotropic structure). The advantage of using this technique is that the contraction in the transverse direction that existed in the previous actuators becomes the expansion improving the actuator performance by about 21% compared to prior counterparts. The available commercial software Abaqus2021 is used for simulation, and its results are verified with the experimental results. A comparative investigation between the presented PMCA and the previous silicone-based counterpart is performed. A meso-macro deformation study is developed experimentally and numerically to justify the improvement of the presented PMCA.

Fibre fragment pollution: source directed intervention through design

This study analyses the difference in fibre fragment pollution generated during the laundering of woven and knit fabrics for clothing and the influence of fabric parameters on the amount of pollution released. 100% polyester single jersey knit and 2/2 twill woven fabrics were created and washed according to AATCC TM212-2021. Results indicated more tightly woven structures released over three times less pollution than looser knit structures, releasing 6.41 mg of fibre fragments per kg of woven fabric (mean ± 1.50 SD, n = 8) compared to 21.21 mg of fibre fragments per kg of knit fabric (mean ± 1.80 SD, n = 8). The first wash for both knit and woven fabrics shed significantly more fibre fragments than subsequent washes. By the fifth wash both fabrics released under a tenth of the amount of pollution released in the first wash. To mitigate fibre fragment pollution that is released by fabrics designed for clothing this work recommends designing out pollution using more tightly constructed fabrics. Furthermore, the implementation of technology in fabric and garment manufacturing processes (e.g. fibre catching devices) should be utilised specifically during first washes allowing pollution to be filtered from the wastewater to stem the flow of contaminants into the environment.

Natural Dyeing of Cotton, Wool and Viscose Fabrics with Sodium Copper Chlorophyllin

This study investigates the optimal dyeing concentrations of cotton, wool, and viscose fabrics with sodium copper chlorophyllin (SCC). Using SSC above the optimal concentration increases the amount of SCC in the wastewater, which is a disadvantage. Pre-finished 100% cotton, wool and viscose 1 x 1 rib knitted fabrics were dyed with varying SCC concentrations. Optimal dyeing concentrations were determined using UV-Vis spectrophotometry, showing dye absorption decreasing as SCC concentration increases. Equilibrium was reached at approximately 7 ml/L for cotton and viscose, and 3 ml/L for wool. Color measurement values and K/S values of the dyed samples were obtained according to the CIELab color system. The K/S values of dyed cotton, viscose, and wool fabrics rose as the concentration of SCC increased, reaching a peak at 9 ml/L for viscose and 12 ml/L for cotton and wool. Rubbing and perspiration fastness were rated good to excellent.